{"id":925,"date":"2012-08-21T12:45:39","date_gmt":"2012-08-21T10:45:39","guid":{"rendered":"http:\/\/oldblogs.uct.ac.za\/blog\/big-bytes\/2012\/08\/21\/molecular-visualization"},"modified":"2019-01-03T08:43:13","modified_gmt":"2019-01-03T06:43:13","slug":"molecular-visualization","status":"publish","type":"post","link":"https:\/\/ucthpc.uct.ac.za\/index.php\/2012\/08\/21\/molecular-visualization\/","title":{"rendered":"Molecular visualization"},"content":{"rendered":"Why is molecular visualization cool?\u00a0 Take a look at this animation from WEHI<\/a>:\r\n
\r\n
\r\n<\/object>\r\n
\r\n
\r\nOne of the molecular visualization tools we support is NAMD.\u00a0 We recently updated our version from 2.7 to 2.9 and compiled it to run with OpenMPI rather than NAMD's own multi processor controler, CHARM.\u00a0 This makes resource requesting and job submission much easier.\u00a0 Below is the native NAMD method of addressing multiple cores in a distributed architecture:\r\n
\r\n
\r\n#PBS -N NAMD-CHARMRUN\r\n#PBS -l nodes=node1:ppn=4+node2:ppn=4+node3:ppn=4+node4:ppn=4+node5:ppn=4\r\ncharmrun namd2 +p20 ++remote-shell ssh ++nodelist machine.file test.namd > charmout.txt\r\n<\/span>\r\n
\r\n
\r\nNow instead of using the above cumbersome method the standard mpirun executable can be called:\r\n
\r\n
\r\n#PBS -N NAMD=MPIRUN\r\n#PBS -l nodes=5:ppn=4:series200\r\nmpirun -hostfile $PBS_NODEFILE namd2 test.namd > mpiout.txt<\/span>\r\n
\r\n
\r\nThis also functions much better with PBStorque as it's designed to work hand in glove with OpenMPI.\u00a0 In the 2nd example you'll note that it's no longer necessary to tell mpirun or namd how many processors are required, it works that out from the job requirements, 5 nodes x 4 cores = 20 cores total.\r\n
\r\n
\r\nBelow is the method we used to compile NAMD with OpenMPI support:<\/strong>\r\n
\r\n
\r\nUnpack NAMD and matching Charm++ source code and enter directory:\r\ntar xzf NAMD_2.9_Source.tar.gz\r\ncd NAMD_2.9_Source\r\ntar xf charm-6.4.0.tar\r\ncd charm-6.4.0<\/span>\r\n
\r\n
\r\nBuild and test the Charm++\/Converse library (MPI version):\r\nenv MPICXX=mpicxx .\/build charm++ mpi-linux-x86_64 --with-production\r\ncd mpi-linux-x86_64\/tests\/charm++\/megatest\r\nmake pgm\r\nmpirun -n 4 .\/pgm\u00a0\u00a0\u00a0 (run as any other MPI program on your cluster)\r\ncd ..\/..\/..\/..\/..<\/span>\r\n
\r\n
\r\nDownload and install TCL and FFTW libraries:\r\n(cd to NAMD_2.9_Source if you're not already there)\r\nwget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/fftw-linux-x86_64.tar.gz<\/span><\/a>\r\n\u00a0 tar xzf fftw-linux-x86_64.tar.gz\r\nmv linux-x86_64 fftw\r\nwget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64.tar.gz<\/span><\/a>\r\n\u00a0 wget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64-threaded.tar.gz<\/span><\/a>\r\n\u00a0 tar xzf tcl8.5.9-linux-x86_64.tar.gz\r\ntar xzf tcl8.5.9-linux-x86_64-threaded.tar.gz\r\nmv tcl8.5.9-linux-x86_64 tcl\r\nmv tcl8.5.9-linux-x86_64-threaded tcl-threaded<\/span>\r\n
\r\n
\r\nSet up build directory and compile:\r\nMPI version: .\/config Linux-x86_64-g++ --charm-arch mpi-linux-x86_64\r\ncd Linux-x86_64-g++\r\nmake<\/span>\r\n
\r\n
\r\nQuick tests using one and two processes (network version):\r\n(this is a 66-atom simulation so don't expect any speedup)\r\n.\/namd2\r\n.\/namd2 src\/alanin\r\n.\/charmrun ++local +p2 .\/namd2\r\n.\/charmrun ++local +p2 .\/namd2 src\/alanin\r\n(for MPI version, run namd2 binary as any other MPI executable)<\/span>\r\n
\r\n
\r\nLonger test using four processes:\r\nwget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/utilities\/apoa1.tar.gz<\/span><\/a>\r\n\u00a0 tar xzf apoa1.tar.gz\r\n.\/charmrun ++local +p4 .\/namd2 apoa1\/apoa1.namd\r\n(FFT optimization will take a several seconds during the first run.)<\/span>\r\n\r\n ","protected":false},"excerpt":{"rendered":"

Why is molecular visualization cool?  Take a look at this animation from WEHI<\/a>: <\/p>\n<\/p>\n

 <\/p>\n

One of the molecular visualization tools we support is NAMD.  We recently updated our version from 2.7 to 2.9 and compiled it to run with OpenMPI rather than NAMD’s own multi processor controler, CHARM.  This makes resource requesting and job submission much easier.  Below is the native NAMD method of addressing multiple cores in a distributed architecture:<\/p>\n

#PBS -N NAMD-CHARMRUN
#PBS -l nodes=node1:ppn=4+node2:ppn=4+node3:ppn=4+node4:ppn=4+node5:ppn=4
charmrun namd2 +p20 ++remote-shell ssh ++nodelist machine.file test.namd > charmout.txt
<\/span><\/p>\n

Now instead of using the above cumbersome method the standard mpirun executable can be called:<\/p>\n

#PBS -N NAMD=MPIRUN
#PBS -l nodes=5:ppn=4:series200
mpirun -hostfile $PBS_NODEFILE namd2 test.namd > mpiout.txt<\/span><\/p>\n

This also functions much better with PBStorque as it’s designed to work hand in glove with OpenMPI.  In the 2nd example you’ll note that it’s no longer necessary to tell mpirun or namd how many processors are required, it works that out from the job requirements, 5 nodes x 4 cores = 20 cores total.<\/p>\n

Below is the method we used to compile NAMD with OpenMPI support:<\/strong><\/p>\n

Unpack NAMD and matching Charm++ source code and enter directory:
  tar xzf NAMD_2.9_Source.tar.gz
  cd NAMD_2.9_Source
  tar xf charm-6.4.0.tar
  cd charm-6.4.0<\/span><\/p>\n

Build and test the Charm++\/Converse library (MPI version):
  env MPICXX=mpicxx .\/build charm++ mpi-linux-x86_64 –with-production
  cd mpi-linux-x86_64\/tests\/charm++\/megatest
  make pgm
  mpirun -n 4 .\/pgm    (run as any other MPI program on your cluster)
  cd ..\/..\/..\/..\/..<\/span><\/p>\n

Download and install TCL and FFTW libraries:
  (cd to NAMD_2.9_Source if you’re not already there)
  wget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/fftw-linux-x86_64.tar.gz<\/span><\/a>
  tar xzf fftw-linux-x86_64.tar.gz
  mv linux-x86_64 fftw
  wget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64.tar.gz<\/span><\/a>
  wget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64-threaded.tar.gz<\/span><\/a>
  tar xzf tcl8.5.9-linux-x86_64.tar.gz
  tar xzf tcl8.5.9-linux-x86_64-threaded.tar.gz
  mv tcl8.5.9-linux-x86_64 tcl
  mv tcl8.5.9-linux-x86_64-threaded tcl-threaded<\/span><\/p>\n

Set up build directory and compile:
  MPI version: .\/config Linux-x86_64-g++ –charm-arch mpi-linux-x86_64
  cd Linux-x86_64-g++
  make<\/span><\/p>\n

Quick tests using one and two processes (network version):
  (this is a 66-atom simulation so don’t expect any speedup)
  .\/namd2
  .\/namd2 src\/alanin
  .\/charmrun ++local +p2 .\/namd2
  .\/charmrun ++local +p2 .\/namd2 src\/alanin
  (for MPI version, run namd2 binary as any other MPI executable)<\/span><\/p>\n

Longer test using four processes:
  wget <\/span>http:\/\/www.ks.uiuc.edu\/Research\/namd\/utilities\/apoa1.tar.gz<\/span><\/a>
  tar xzf apoa1.tar.gz
  .\/charmrun ++local +p4 .\/namd2 apoa1\/apoa1.namd
  (FFT optimization will take a several seconds during the first run.)<\/span><\/p>\n

 <\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[],"yoast_head":"\nMolecular visualization - UCT HPC<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ucthpc.uct.ac.za\/index.php\/2012\/08\/21\/molecular-visualization\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Molecular visualization - UCT HPC\" \/>\n<meta property=\"og:description\" content=\"Why is molecular visualization cool?  Take a look at this animation from WEHI:  One of the molecular visualization tools we support is NAMD.  We recently updated our version from 2.7 to 2.9 and compiled it to run with OpenMPI rather than NAMD's own multi processor controler, CHARM.  This makes resource requesting and job submission much easier.  Below is the native NAMD method of addressing multiple cores in a distributed architecture:#PBS -N NAMD-CHARMRUN#PBS -l nodes=node1:ppn=4+node2:ppn=4+node3:ppn=4+node4:ppn=4+node5:ppn=4charmrun namd2 +p20 ++remote-shell ssh ++nodelist machine.file test.namd > charmout.txtNow instead of using the above cumbersome method the standard mpirun executable can be called:#PBS -N NAMD=MPIRUN#PBS -l nodes=5:ppn=4:series200mpirun -hostfile $PBS_NODEFILE namd2 test.namd > mpiout.txtThis also functions much better with PBStorque as it's designed to work hand in glove with OpenMPI.  In the 2nd example you'll note that it's no longer necessary to tell mpirun or namd how many processors are required, it works that out from the job requirements, 5 nodes x 4 cores = 20 cores total.Below is the method we used to compile NAMD with OpenMPI support:Unpack NAMD and matching Charm++ source code and enter directory:  tar xzf NAMD_2.9_Source.tar.gz  cd NAMD_2.9_Source  tar xf charm-6.4.0.tar  cd charm-6.4.0Build and test the Charm++\/Converse library (MPI version):  env MPICXX=mpicxx .\/build charm++ mpi-linux-x86_64 --with-production  cd mpi-linux-x86_64\/tests\/charm++\/megatest  make pgm  mpirun -n 4 .\/pgm    (run as any other MPI program on your cluster)  cd ..\/..\/..\/..\/..Download and install TCL and FFTW libraries:  (cd to NAMD_2.9_Source if you're not already there)  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/fftw-linux-x86_64.tar.gz  tar xzf fftw-linux-x86_64.tar.gz  mv linux-x86_64 fftw  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64.tar.gz  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64-threaded.tar.gz  tar xzf tcl8.5.9-linux-x86_64.tar.gz  tar xzf tcl8.5.9-linux-x86_64-threaded.tar.gz  mv tcl8.5.9-linux-x86_64 tcl  mv tcl8.5.9-linux-x86_64-threaded tcl-threadedSet up build directory and compile:  MPI version: .\/config Linux-x86_64-g++ --charm-arch mpi-linux-x86_64  cd Linux-x86_64-g++  makeQuick tests using one and two processes (network version):  (this is a 66-atom simulation so don't expect any speedup)  .\/namd2  .\/namd2 src\/alanin  .\/charmrun ++local +p2 .\/namd2  .\/charmrun ++local +p2 .\/namd2 src\/alanin  (for MPI version, run namd2 binary as any other MPI executable)Longer test using four processes:  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/utilities\/apoa1.tar.gz  tar xzf apoa1.tar.gz  .\/charmrun ++local +p4 .\/namd2 apoa1\/apoa1.namd  (FFT optimization will take a several seconds during the first run.) \" \/>\n<meta property=\"og:url\" content=\"https:\/\/ucthpc.uct.ac.za\/index.php\/2012\/08\/21\/molecular-visualization\/\" \/>\n<meta property=\"og:site_name\" content=\"UCT HPC\" \/>\n<meta property=\"article:published_time\" content=\"2012-08-21T10:45:39+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2019-01-03T06:43:13+00:00\" \/>\n<meta name=\"author\" content=\"Andrew Lewis\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Andrew Lewis\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/ucthpc.uct.ac.za\/index.php\/2012\/08\/21\/molecular-visualization\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/ucthpc.uct.ac.za\/index.php\/2012\/08\/21\/molecular-visualization\/\"},\"author\":{\"name\":\"Andrew Lewis\",\"@id\":\"https:\/\/ucthpc.uct.ac.za\/#\/schema\/person\/c183ad1c0a1063124a72d63963ae9c7e\"},\"headline\":\"Molecular 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of using the above cumbersome method the standard mpirun executable can be called:#PBS -N NAMD=MPIRUN#PBS -l nodes=5:ppn=4:series200mpirun -hostfile $PBS_NODEFILE namd2 test.namd > mpiout.txtThis also functions much better with PBStorque as it's designed to work hand in glove with OpenMPI.  In the 2nd example you'll note that it's no longer necessary to tell mpirun or namd how many processors are required, it works that out from the job requirements, 5 nodes x 4 cores = 20 cores total.Below is the method we used to compile NAMD with OpenMPI support:Unpack NAMD and matching Charm++ source code and enter directory:  tar xzf NAMD_2.9_Source.tar.gz  cd NAMD_2.9_Source  tar xf charm-6.4.0.tar  cd charm-6.4.0Build and test the Charm++\/Converse library (MPI version):  env MPICXX=mpicxx .\/build charm++ mpi-linux-x86_64 --with-production  cd mpi-linux-x86_64\/tests\/charm++\/megatest  make pgm  mpirun -n 4 .\/pgm    (run as any other MPI program on your cluster)  cd ..\/..\/..\/..\/..Download and install TCL and FFTW libraries:  (cd to NAMD_2.9_Source if you're not already there)  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/fftw-linux-x86_64.tar.gz  tar xzf fftw-linux-x86_64.tar.gz  mv linux-x86_64 fftw  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64.tar.gz  wget http:\/\/www.ks.uiuc.edu\/Research\/namd\/libraries\/tcl8.5.9-linux-x86_64-threaded.tar.gz  tar xzf tcl8.5.9-linux-x86_64.tar.gz  tar xzf tcl8.5.9-linux-x86_64-threaded.tar.gz  mv tcl8.5.9-linux-x86_64 tcl  mv tcl8.5.9-linux-x86_64-threaded tcl-threadedSet up build directory and compile:  MPI version: .\/config Linux-x86_64-g++ --charm-arch mpi-linux-x86_64  cd Linux-x86_64-g++  makeQuick tests using one and two processes (network version):  (this is a 66-atom simulation so don't expect any speedup)  .\/namd2  .\/namd2 src\/alanin  .\/charmrun ++local +p2 .\/namd2  .\/charmrun ++local +p2 .\/namd2 src\/alanin  (for MPI version, run namd2 binary as any other MPI 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